The DOI matches its Crossref record; 79 of the 79 references it cites were found in a registry or an index.
Insight from CMIP6 SSP-RCP scenarios for future drought characteristics in China
Abstract
Abstract In this paper, future drought characteristics (frequency, duration and intensity) over China are analysed by using four climate models from CMIP6 under the seven SSP-RCP (shared socioeconomic pathway-representative concentration pathway) scenarios (SSP119, SSP126, SSP434, SSP245, SSP460, SSP370, and SSP585) for three defined periods of 2021–2040 (near-term), 2041–2060 (mid-term) and 2081–2100 (long-term). The corresponding four climate models output from CMIP5 are also used to conduct a comparison analysis between CMIP5 and CMIP6 to address the improvements added to CMIP6 in terms of drought identification. The drought characteristics are identified by applying the standardized precipitation-evapotranspiration index (SPEI) at a 12-month timescale and run theory. The results show that CMIP6 has a robust capability to capture historical (1986–2005) drought characteristics. For the future period of 2021–2040, the decrease in precipitation and increase in potential evapotranspiration will lead to continuous dry conditions in the upper and middle Yangtze River basin and eastern Pearl River basin. Relative to the reference period, drought events will be more frequent and severe with longer durations in the Northwest River basins and middle Yangtze River basin. Furthermore, higher emissions signify a greater increase in drought frequency and intensity in the long-term period. Except for the SSP585 scenario, the lower emission scenario corresponds to the higher drought duration soon and in the mid-21st century (2021–2060). This finding is regarded as a “strange phenomenon”, which cannot be detected by the previous CMIP5-based emission scenarios (RCP2.6, RCP4.5 and the unlikely pathway RCP8.5). Therefore, additional “possible future”-based scenarios (SSP119, SSP126, SSP434, SSP245, SSP460, and SSP370) should be included in extreme climate studies, especially for the near future and mid-21st century. Notably, compared with CMIP5, the reduced biases in drought characteristics are more likely associated with improvements in the representation of physical processes in climate models from CMIP6. The results of this study could provide a basis for the development of drought adaptation measures over China.
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Cites
An Overview of CMIP5 and the Experiment Design
Taylor, K. E., Stouffer, R. J., & Meehl, G. A. (2012) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-11-00094.1 · Cited by 14,052
Eyring, V., Bony, S., Meehl, G. A., Senior, C. A., Stevens, B., Stouffer, R. J., & Taylor, K. E. (2016) · Geoscientific Model Development · doi:10.5194/gmd-9-1937-2016 · Cited by 11,981
Vicente-Serrano, S. M., Beguería, S., & López-Moreno, J. I. (2010) · Journal of Climate · doi:10.1175/2009jcli2909.1 · Cited by 9,493
The representative concentration pathways: an overview
van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J.-F., et al. (2011) · Climatic Change · doi:10.1007/s10584-011-0148-z · Cited by 7,741
(1993) · Cited by 7,699
The next generation of scenarios for climate change research and assessment
Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., van Vuuren, D. P., Carter, T. R., Emori, S., Kainuma, M., Kram, T., et al. (2010) · Nature · doi:10.1038/nature08823 · Cited by 6,467
The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6
O'Neill, B. C., Tebaldi, C., van Vuuren, D. P., Eyring, V., Friedlingstein, P., Hurtt, G., Knutti, R., Kriegler, E., Lamarque, J.-F., Lowe, J., et al. (2016) · Geoscientific Model Development · doi:10.5194/gmd-9-3461-2016 · Cited by 5,241
Climate Extremes: Observations, Modeling, and Impacts
Easterling, D. R., Meehl, G. A., Parmesan, C., Changnon, S. A., Karl, T. R., & Mearns, L. O. (2000) · Science · doi:10.1126/science.289.5487.2068 · Cited by 4,867
Increasing drought under global warming in observations and models
Dai, A. (2013) · Nature Climate Change · doi:10.1038/nclimate1633 · Cited by 4,762
Research works printed but not linked: 6
- Gao, 2012, Uncertainties in monsoon precipitation projections over China: results from two high-resolution RCM simulations, Clim. Res., 52, 213, 10.3354/cr01084 · doi:10.3354/cr01084
- Laurie, 2020, How well do CMIP6 historical runs match observed Northeast US precipitation and extreme precipitation-related circulation, J. Clim., 33, 9835, 10.1175/JCLI-D-19-1025.1 · doi:10.1175/jcli-d-19-1025.1
- Liang, 2017, Projection of drought hazards in China during twenty-first century, Theor. Appl. Climatol., 133, 331, 10.1007/s00704-017-2189-3 · doi:10.1007/s00704-017-2189-3
- Nature Climate Change, 2019, The CMIP6 landscape, Nat. Clim. Chang., 9
- Yin, 2009, Attribution analyses of potential evapotranspiration changes in China since the 1960s, Theor. Appl. Climatol., 101, 19, 10.1007/s00704-009-0197-7 · doi:10.1007/s00704-009-0197-7
- Zhai, 2010, Dryness/wetness variations in ten large river basins of China during the first 50 years of the 21st century, Quat. Int., 226, 101, 10.1016/j.quaint.2010.01.027 · doi:10.1016/j.quaint.2010.01.027
Cited by
Song, Y. H., Shahid, S., & Chung, E. (2022) · International Journal of Climatology · doi:10.1002/joc.7386 · Cited by 45
Future Hydrological Drought Analysis Considering Agricultural Water Withdrawal Under SSP Scenarios
Kim, J. H., Sung, J. H., Shahid, S., & Chung, E.-S. (2022) · Water Resources Management · doi:10.1007/s11269-022-03116-1 · Cited by 38
Metadata
- Authors
- Su, B., Huang, J., Mondal, S. K., Zhai, J., Wang, Y., Wen, S., Gao, M., Lv, Y., Jiang, S., Jiang, T., & Li, A.
- Venue
- Atmospheric Research
- Publisher
- Elsevier BV
- Published
- 2021-03
- Volume
- 250
- Pages
- 105375
- ISSN
- 0169-8095 (ISSN-L)
- OpenAlex
- W3108729183
- Cited by
- 419
- References
- 79
- FWCI
- 14.91
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China (2019YFC1510203, GZ 1486)
- Deutsche Forschungsgemeinschaft
- Nanjing University of Information Science and Technology
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- Su, B., Huang, J., Mondal, S. K., Zhai, J., Wang, Y., Wen, S., Gao, M., Lv, Y., Jiang, S., Jiang, T., & Li, A. (2021). Insight from CMIP6 SSP-RCP scenarios for future drought characteristics in China. Atmospheric Research. https://doi.org/10.1016/j.atmosres.2020.105375
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